Improving O3, PM25 and NO2 Surface Fields by Optimally Interpolating Updatable MOS Forecasts

被引：2

作者：

Antonopoulos, Stavros ^{[1
]}

Montpetit, Jacques ^{[1
]}

Fortin, Vincent ^{[2
]}

Roy, Guy ^{[3
]}

机构：

[1] Environm Canada, Weather Elements Sect, Dorval, PQ, Canada

[2] Environm Canada, Meteorol Res Div, Dorval, PQ, Canada

[3] Environm Canada, Meteorol Serv Canada, Montreal, PQ, Canada

来源：

AIR POLLUTION MODELING AND ITS APPLICATION XXII | 2014年

关键词：

Particulate matter; Ozone; Nitrogen dioxide; Updatable MOS; UMOS; MLR; Post-processing; Krigging; Optimal interpolation;

D O I：

10.1007/978-94-007-5577-2_40

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Updatable Model Output Statistics (UMOS) (Wilson JW, Vallee M, Weather Forecast, 17:206-222, 2001) methodology in air-quality forecasting (UMOS-AQ) has shown great ability to improve direct model output. The UMOS-AQ (Antonopoulos S, Bourgouin P, Montpetit J, Croteau G, Forecasting O-3, PM25 and NO2 hourly spot concentrations using an updateable MOS methodology. In: Proceedings for the 31st NATO/SPS international technical meeting on air pollution modeling and its application, Torino, Italy, pp 309-314, 2010) system produces one equation for each station, predictand, model run, forecast hour and season. A limitation of the method however is the fact that we only obtain point forecasts. An optimal interpolation solution on the UMOS-AQ forecasts using Simple Krigging is presented in which the model's output is used as a trial field. The parametrization chosen is such that the radius of influence is approximately two grid points with most of the weight coming from the UMOS-AQ forecasts. Preliminary results showed significant improvements over the model's forecasts in regions with a high density of observation stations.

引用

页码：233 / 237

页数：5